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About the Role
Build and maintain the platform that powers how the world's leading brands measure the true causal impact of their marketing spend. Our Science Platform runs geo-based experiments across 100+ customers, processes daily analysis pipelines, and delivers statistical results that directly drive budget decisions worth millions of dollars.
Responsibilities
- Build and evolve the data pipelines that fetch, aggregate, and transform KPI data from BigQuery across multiple geographies and granularities
- Extend and maintain the statistical estimation library — implement new estimators, improve standard error methods, and optimize performance for large panel datasets
- Improve the Metaflow-based analysis orchestration system that schedules and executes thousands of daily experiment analyses on Kubernetes
- Design for reliability: build monitoring, alerting, and self-healing patterns for pipelines that run autonomously every day
- Collaborate closely with applied scientists to translate research prototypes into production-grade code with proper testing, error handling, and observability
- Work with product engineers to ensure analysis results are published correctly and flow cleanly into the customer-facing API and frontend
- Use AI development tools as part of your daily workflow to accelerate delivery and explore solutions
- Participate in on-call rotation and own the operational health of the science platform systems
Requirements
- 3+ years of experience building and shipping production software systems
- Strong Python proficiency — you write clean, well-tested Python and are comfortable with the ecosystem (pandas, numpy, pytest, poetry)
- Experience with data-intensive applications: you've worked with large datasets, data pipelines, or ETL systems and understand the tradeoffs
- Experience with SQL and analytical databases (BigQuery, Snowflake, or similar) — you can write performant queries and understand how warehouse-scale data processing works
- Comfort with cloud-native environments (GCP preferred): you understand how to deploy, monitor, and operate services in production
- Ability to collaborate productively with scientists and researchers — you don't need a PhD, but you should be comfortable reading statistical code, understanding experimental design concepts, and asking good questions
- Excellent communication skills — you can explain technical tradeoffs clearly and work effectively across disciplines
Skills
- Python
- pandas
- numpy
- pytest
- poetry
- SQL
- BigQuery
- Snowflake
- GCP
- Metaflow
- Airflow
- Dagster
- Prefect
- Claude
- Cursor
- Copilot
- scipy
- scikit-learn
- Bayesian methods
- Kubernetes
- Pub/Sub
- message queues
- experimentation platforms
- A/B testing infrastructure
- causal inference systems
Location
- San Francisco
- Seattle
- New York City
Work Type
- Onsite
- Hybrid
Experience Level
- 3+ years of experience
Benefits
- Flexible PTO
- Equity
- Top of the line health, dental, and vision insurance
- WFH stipend
- Events & Offsites
- Free Lunch
- New Parent Leave
About the Company
- Haus is the incrementality platform leading brands trust to optimize billions in ad spend worldwide.
- Using frontier causal inference-based econometric models to run experiments, we help brands measure the business impact of marketing, pricing, and promotions with scientific precision.
- Over $360B is spent annually on paid advertising in the US alone, and the famous quote “half the money I spend on advertising is wasted; the trouble is I don’t know which half” still rings true.
- Haus helps marketers identify which half, and reallocate it to maximize growth.
- With a founding team of former product managers, economists, and engineers from Google, Netflix, Meta, and Amazon, we make high-quality decision science, incrementality testing, and causal marketing mix modeling accessible to businesses of all sizes—automating the heavy lifting of experiment design, data processing, and insights generation.
- Haus works with leading brands like FanDuel, Sonos, and Dr. Squatch, delivering ROI gains as high as 30x.
- Haus is well-capitalized and backed by top-tier VCs, including Insight Partners, Baseline Ventures, Haystack, and others.
- We're honored that Haus has once again been recognized by LinkedIn as a 2025 Top Startup!
- We’re a high-performance, low-ego team operating in a fast-moving environment.
- We care deeply about our customers and expect everyone to take full ownership of their work — this is a place where high expectations fuel even higher growth.
- If you thrive in ambiguity, take pride in raising the bar, and want to work alongside top-tier peers who challenge and support you, you'll find unmatched opportunities here.
- If you're looking for predictability or rigid structure or you prefer order-taking to go-getting, we’re probably not the right fit — and that’s okay.
- We work in small, mission-driven teams that prioritize inclusion, collaboration, and growth over hierarchy or red tape.
Equal Opportunity
- Haus is an equal opportunity employer. We make hiring decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.
- We believe diverse perspectives make us stronger and are committed to an inclusive culture where everyone feels seen, heard, and empowered to contribute. Bring your authentic self — we would love to hear from you.